scholarly journals Analysis of Iterative Learning Control for a Class of Linear Discrete-Time Switched Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Xuan Yang ◽  
Xiaoe Ruan
Keyword(s):  
Discrete Time ◽  
Switched Systems ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning ◽  
Switched System ◽  
Time Interval ◽  
Bounded Noise ◽  
Arbitrary Switching ◽  
Control Scheme

An iterative learning control scheme is applied to a class of linear discrete-time switched systems with arbitrary switching rules. The application is based on the assumption that the switched system repetitively operates over a finite time interval. By taking advantage of the super vector approach, convergence is discussed when noise is free and robustness is analyzed when the controlled system is disturbed by bounded noise. The analytical results manifest that the iterative learning control algorithm is feasible and effective for the linear switched system. To support the theoretical analysis, numerical simulations are made.

scholarly journals A PD-Type Iterative Learning Control for a Class of Switched Discrete-Time Systems with Model Uncertainties and External Noises

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Xuan Yang
Keyword(s):  
Discrete Time ◽  
Switched Systems ◽  
Iterative Learning Control ◽  
Control Algorithm ◽  
Learning Control ◽  
Iterative Learning ◽  
Time Interval ◽  
Monotone Convergence ◽  
Model Uncertainties ◽  
Time Systems

A PD-type iterative learning control algorithm is applied to a class of linear discrete-time switched systems for tracking desired trajectories. The application is based on assumption that the switched systems repetitively operate over a finite time interval and the switching rules are arbitrarily prespecified. By taking advantage of the super-vector approach, a sufficient condition of the monotone convergence of the algorithm is deduced when both the model uncertainties and the external noises are absent. Then the robust monotone convergence is analyzed when the model uncertainties are present and the robustness against the bounded external noises is discussed. The analysis manifests that the proposed PD-type iterative learning control algorithm is feasible and effective when it is imposed on the linear switched systems specified by the arbitrarily preset switching rules. The attached simulations support the feasibility and the effectiveness.

Iterative Learning Control for a Class of Linear Discrete-time Switched Systems

2014 ◽  
Vol 39 (9) ◽  
pp. 1564-1569 ◽  
Author(s):  
Xu-Hui BU ◽  
Fa-Shan YU ◽  
Zhong-Sheng HOU ◽  
Fu-Zhong WANG
Keyword(s):  
Discrete Time ◽  
Switched Systems ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning

D-type iterative learning control without resetting condition for robot manipulators

Robotica ◽  
2011 ◽  
Vol 29 (7) ◽  
pp. 975-980 ◽  
Author(s):  
Farah Bouakrif
Keyword(s):  
Iterative Learning Control ◽  
Robot Manipulators ◽  
Learning Control ◽  
Iterative Learning ◽  
Time Interval ◽  
Initial State ◽  
External Disturbances ◽  
Repetitive Tasks ◽  
Control Scheme ◽  
Topological Measure

SUMMARYThis paper deals with iterative learning control (ILC) design to solve the trajectory tracking problem for rigid robot manipulators subject to external disturbances, and performing repetitive tasks. A D-type ILC is presented with an initial condition algorithm, which gives the initial state value in each iteration automatically. Thus, the resetting condition (the initial state error is equal to zero) is not required. The λ-norm is adopted as the topological measure in our proof of the asymptotic stability of this control scheme, over the whole finite time-interval, when the iteration number tends to infinity. Simulation results are presented to illustrate the effectiveness of the proposed control scheme.

Iterative Learning Control for a Class of Linear Discrete-time Switched Systems

2013 ◽  
Vol 39 (9) ◽  
pp. 1564-1569 ◽  
Author(s):  
Xu-Hui BU ◽  
Fa-Shan YU ◽  
Zhong-Sheng HOU ◽  
Fu-Zhong WANG
Keyword(s):  
Discrete Time ◽  
Switched Systems ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning
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